Mr. Adamu Abubakar Sani | Machine Learning | Best Researcher Award

Mr. Adamu Abubakar Sani | Machine Learning | Best Researcher Award

Adamu Abubakar Sani at Universiti Teknologi PETRONAS, Malaysia

👨‍🎓 Profiles

Google Scholar

Publications

A Multi-level Classification Model for Corrosion defects in Oil and Gas Pipelines Using Meta-Learner Ensemble (MLE) Techniques

  • Authors: Adamu Sani Abubakar, Mohamed Mubarak Abdul Wahab, Nasir Shafiq, Kamaludden Usman, Nasir Khan, Adamu Tafida, Arsalan Khan
  • Journal: Journal of Pipeline Science and Engineering
  • Year: 2024

A Review of Eco-Friendly Road Infrastructure Innovations for Sustainable Transportation

  • Authors: Adamu Tafida, Wesam Salah Alaloul, Noor Amila Bt Wan Zawawi, Muhammad Ali Musarat, Adamu Sani Abubakar
  • Journal: Infrastructures
  • Year: 2024

Design and modeling the compressive strength of high-performance concrete with silica fume: a soft computing approach

  • Authors: Abiola Usman Adebanjo, Nasir Shafiq, Siti Nooriza Abd Razak, Vicky Kumar, Syed Ahmad Farhan, Priyanka Singh, Adamu Sanni Abubakar
  • Journal: Soft Computing
  • Year: 2024

Systematic Literature Review and Scientometric Analysis on the Advancements in Electrically Conductive Asphalt Technology for Smart and Sustainable Pavements

  • Authors: Arsalaan Khan Yousafzai, Muslich Hartadi Sutanto, Muhammad Imran Khan, Nura Shehu Aliyu Yaro, Abdullah O Baarimah, Nasir Khan, Abdul Muhaimin Memon, Adamu Sani Abubakar
  • Journal: Transportation Research Record
  • Year: 2024

Integrating Life Cycle Cost Analysis into Pipeline Asset Integrity Management: A Comprehensive Approach in Decision Support Systems

  • Authors: Adamu Sani Abubakar, Mohamed Mubarak Bin Abdul Wahab, Nasir Shafiq, Kamaluddeen U Danyaro, Abiola Usman Adebanjo
  • Journal: Journal of Hunan University Natural Sciences
  • Year: 2024

Assist Prof Dr. Sina Fard Moradinia | Machine Learning | Editorial Board Member

Assist Prof Dr. Sina Fard Moradinia | Machine Learning | Editorial Board Member

Sina Fard Moradinia at Islamic Azad University, Iran

👨‍🎓 Profiles

Scopus

Orcid

Summary

Dr. Sina Fard Moradinia is a dedicated Assistant Professor in Civil Engineering with over 20 years of experience specializing in water resources management. He has made significant contributions to both academia and industry through research, teaching, and numerous projects. Dr. Moradinia has been involved in leadership roles, including serving as the Head of the Water Resources Management Working Group and a member of various scientific councils and committees. He is also an accomplished author with expertise in project management, hydraulic structures, and innovative water management techniques.

Education

  • Ph.D. in Civil Engineering (Water Resources) – Iran University of Science and Technology, Tehran, Iran, 2014

💼 Professional Experience

  • Assistant Professor – Islamic Azad University, Tabriz (2002–Present)
  • Head of Water Resources Management Working Group – East Azerbaijan Province Elite Foundation
  • University Representative – Skills Training and Career Counseling Center
  • Civil Engineering Expert – Faraz Ab Consulting Engineers
  • Engineering Services Expert – Dam and Network Activities, River Engineering

🔬 Research Interests

Dr. Moradinia’s research interests focus on water resources management, hydraulic structures, and construction project optimization. His work spans advanced machine learning applications in flood risk assessment, time and cost management in dam projects, and BIM integration in civil engineering. He is also actively engaged in addressing environmental issues such as controlling dust storms in the Urmia Lake basin.

 

Publications

Economic and environmental analysis of EVs’ in urban transportation using system dynamics

  • Authors: Azarnoosh, Z., Moradinia, S.F., Golchin, B., Jani, R.
  • Journal: Sustainable Futures
  • Year: 2024

A novel approach to flood risk zonation: integrating deep learning models with APG in the Aji Chay catchment

  • Authors: Bina, A.A., Moradinia, S.F.
  • Journal: Aqua Water Infrastructure, Ecosystems and Society
  • Year: 2024

Wavelet–ANN hybrid model evaluation in seepage prediction in nonhomogeneous earthen dams

  • Authors: Fatehi-Nobarian, B., Fard Moradinia, S.
  • Journal: Water Practice and Technology
  • Year: 2024

Time and Cost Management in Water Resources Projects Utilizing the Earned Value Method

  • Authors: Hussein, A.R., Moradinia, S.F.
  • Journal: Journal of Studies in Science and Engineering
  • Year: 2024

The prediction of precipitation changes in the Aji-Chay watershed using CMIP6 models and the wavelet neural network

  • Authors: Khoramabadi, F., Moradinia, S.F.
  • Journal: Journal of Water and Climate Change
  • Year: 2024

Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Professor at Zaporizhzhia State Medical University, Ukraine

Profiles

Scopus

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Google Scholar

📚 Summary

Prof. Igor Fedorovich Belenichev is a distinguished Full Professor and Head of the Department of Pharmacology and Medical Formulation at Zaporizhzhia State Medical University. Renowned for his innovative research in neuroprotection and pharmacology, he is a laureate of the Cabinet of Ministers of Ukraine Prize for the development and implementation of groundbreaking technologies.

Education

  • Zaporizhzhia State Medical Institute (1988): Graduated with a degree in medicine.
  • Postgraduate studies (1988), professor assistant (1991), senior teacher (1999), associate professor (2004), and full professor (2006).

💼 Professional Experience

  • Zaporizhzhia State Medical University: Head of the Department of Pharmacology and Medical Formulation since 2005.
  • Main Scientific Researcher at «Pharmatrone» (since 1993).
  • Head of the regional branch of the Association of Pharmacologists of Ukraine.
  • Co-worker of the regional group of the National Expert Centre of the Ministry of Health of Ukraine.

🔬 Research Interests

Prof. Belenichev’s research focuses on the molecular and biochemical mechanisms of ischemic brain damage and the development of effective neuroprotectors. His work explores the roles of reactive oxygen and nitrogen species, thiol-disulfide systems, pro-/anti-apoptotic proteins, estrogen receptors, and endogenous neuroprotection factors. He also investigates drugs for CNS pathologies and effective neuro- or cardioprotectors from derivatives of 1,2,4-triazole, chinazoline, and xanthine.

🏆 Achievements

  • Scientific Works: Authored and co-authored 715 scientific publications.
  • Patents: Holder of 182 patents in Ukraine and the Russian Federation.
  • Theses: Supervised 3 Dr. Habs and 7 Ph.D. theses.
  • Drug Development: Contributed to the creation of drugs like Thiotriazoline, Thiocetam, and Thiodarone.
  • Awards: Token of the Bibliographical Society of America (2003), Regional Program “Zoryaniy Shlyakh” Prize (2000), and Cabinet of Ministers of Ukraine Prize (2017).

 

Publications

5+1-Heterocyclization as preparative approach for carboxy-containing triazolo[1,5-c]quinazolines with anti-inflammatory activity

  • Authors: Krasovska, Natalya; Berest, Galina; Belenichev, Igor; Severina, Hanna; Nosulenko, Inna; Voskoboinik, Oleksii; Okovytyy, Sergiy; Kovalenko, Serhii
  • Journal: European Journal of Medicinal Chemistry
  • Year: 2024

Beta-Blockers of Different Generations: Features of Influence on the Disturbances of Myocardial Energy Metabolism in Doxorubicin-Induced Chronic Heart Failure in Rats

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Biomedicines
  • Year: 2024

Characteristics of HIF-1α and HSP70 mRNA Expression, Level, and Interleukins in Experimental Chronic Generalized Periodontitis

  • Authors: Parkhomenko Daria; Igor Belenichev; Kuchkovskyi Oleh; Ryzhenko Victor
  • Journal: MicroRNA
  • Year: 2024

Comparative Analysis of the Effect of Beta Blockers of Different Generations on the Parameters of Myocardial Energy Metabolism in Experimental Doxorubicin-Induced Chronic Heart Failure

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Preprint
  • Year: 2024

Development and Optimization of Nasal Composition of a Neuroprotective Agent for Use in Neonatology after Prenatal Hypoxia

  • Authors: Igor Belenichev; Olena Aliyeva; Bogdan Burlaka; Kristina Burlaka; Oleh Kuchkovskyi; Dmytro Savchenko; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Pharmaceuticals
  • Year: 2024

Prof. Hua Zhang | Machine Learning | Best Researcher Award

Prof. Hua Zhang | Machine Learning | Best Researcher Award

Professor at Wuhan University of Science and Technology, China

Profiles

Scopus

Research Gate

Summary:

Prof. Hua Zhang is a distinguished professor at Wuhan University of Science and Technology (WUST), specializing in clean steel production technology, numerical simulation, and the development of iron-based amorphous alloys. With a Ph.D. in Metallurgical Engineering, he has made significant contributions to steelmaking technology, securing multiple prestigious awards, including provincial science and technology awards and the Baosteel Outstanding Teacher Award. As the vice dean of the School of Materials Science at WUST, Dr. Zhang has published over 100 papers and holds numerous patents.

Education

  • Ph.D. in Metallurgical Engineering (2012)

💼 Professional Experience

  • Professor, Wuhan University of Science and Technology (2019–Present)
  • Postdoctoral Researcher, MCC Continuous Casting Technology Engineering Co., Ltd. (2015–2017)
  • Vice Dean, School of Materials Science, WUST

🔬 Research Interests

  • Clean steel production technology
  • Continuous casting new technology
  • Numerical simulation
  • Iron-based amorphous soft magnetic alloys
  • Secondary utilization of metallurgical resources

 

Publications

Modulating Fe/P Ratios in Fe-P Alloy through Smelting Reduction for Long-Term Electrocatalytic Overall Water Splitting

  • Authors: Zhang, T., Ren, X., Mo, S., Zhang, H., Ni, H.
  • Journal: Journal of Materials Science and Technology
  • Year: 2024
  • Authors: Li, J., Wu, G., Fang, Q., Zhang, H., Ni, H.
  • Journal: Journal of the Taiwan Institute of Chemical Engineers
  • Year: 2024

Investigation on the Characteristics of Porosity, Melt Pool in 316L Stainless Steel Manufactured by Laser Powder Bed Fusion

  • Authors: Liu, C.-S., Xue, X., Wang, Y., Xiong, L., Ni, H.-W.
  • Journal: Journal of Materials Research and Technology
  • Year: 2024

Suppression of Free-Surface Vortex in Tundish by Rotating Stopper-Rod and Its Impact on Multiphase Flow in Mold

  • Authors: Huang, K., Zhang, H., Lu, P., Fang, Q., Ni, H.
  • Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
  • Year: 2024

Optimization of Multiphase Flow and Initial Solidification Behaviors in a Stainless Steel Mold by SEN Design

  • Authors: Gao, F., Fang, Q., Zha, W., Zhang, H., Ni, H.
  • Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
  • Year: 2024

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Doctorate at University of Aveiro , Portugal

Profiles

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Google Scholar

Academic Background

Dr. Kais Iben Nassar is a researcher with a focus on Condensed Matter Physics and Computational Chemistry. He completed his PhD in Physics of Condensed Materials in 2022 through a joint program between the University of Aveiro, Portugal, and the University of Sfax, Tunisia. Dr. Nassar is renowned for his work in materials science, particularly in the study of 2D materials like MXenes and their applications in energy storage and catalysis.

Education

  • PhD in Physics of Condensed Materials
    Université de Sfax & Universidade de Aveiro (2022)
    Achieved with highest honors.
  • Master’s in Condensed Matter Physics
    Université de Sfax (2018)
    Graduated with distinction.
  • Fundamental License in Physics-Chemistry
    Université de Sfax (2016)
    Graduated with distinction.

Professional Experience

  • Postdoctoral Researcher
    Universidade de Aveiro, CICECO (2023 – Present)
    Focus on MXenes catalysts and computational chemistry.
  • Researcher
    Université de Sfax & Universidade de Aveiro (2018 – 2021)
    Conducted research on perovskites and materials science.
  • Invited Assistant Professor
    Université de Sfax (2021 – 2022)
    Taught and mentored students in physics and chemistry.

🔬 Research Interests

Dr. Nassar’s research interests encompass Condensed Materials Physics, nano-materials, computational chemistry, and machine learning. His work includes investigating the properties of 2D materials such as MXene, exploring their potential in energy storage, catalysis, and electronics. He is actively engaged in the preparation and characterization of new perovskite ceramics and the study of their structural, electrical, and magnetic properties. Dr. Nassar is also a member of the European Materials Acceleration Center for Energy (EU-MACE) under the COST Action CA22123.

 Publications

Tailoring of structural, morphological, electrical, and magnetic properties of LaMn1−xFexO3 ceramics
  • Authors: Thakur, P., Nassar, K.I., Kumar, D., Essid, M., Lal, M.
  • Journal: RSC Advances
  • Year: 2024
Structural, electrical properties of bismuth and niobium-doped LaNiO3 perovskite obtained by sol–gel route for future electronic device applications
  • Authors: Nassar, K.I., Benamara, M., Kechiche, L., Teixeira, S.S., Graça, M.P.F.
  • Journal: Indian Journal of Physics
  • Year: 2024
Investigating Fe-doped Ba0.67Ni0.33Mn1−xFexO3 (x = 0, 0.2) ceramics: insights into electrical and dielectric behaviors
  • Authors: Tayari, F., Iben Nassar, K., Algessair, S., Hjiri, M., Benamara, M.
  • Journal: RSC Advances
  • Year: 2024
Sol–gel synthesized (Bi0.5Ba0.5Ag)0.5 (NiMn)0.5O3 perovskite ceramic: An exploration of its structural characteristics, dielectric properties and electrical conductivity
  • Authors: Tayari, F., Iben Nassar, K., Benamara, M., Soreto Teixeira, S., Graça, M.P.F.
  • Journal: Ceramics International
  • Year: 2024
Study of Electrical and Dielectric Behaviors of Copper-Doped Zinc Oxide Ceramic Prepared by Spark Plasma Sintering for Electronic Device Applications
  • Authors: Benamara, M., Iben Nassar, K., Rivero-Antúnez, P., Serrà, A., Esquivias, L.
  • Journal: Nanomaterials
  • Year: 2024

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Doctorate at Heilongjiang University of Science and Technology, China

Profiles

Scopus

Orcid

Academic Background

Dr. Na Yi, born in June 1997 in Acheng, Harbin, is an Associate Professor and a committed member of the Communist Party of China. With a strong academic foundation in Electrical Engineering and Automation, she has quickly risen as a prominent figure in the field of Petroleum and Natural Gas Engineering.

Education

Dr. Na Yi graduated with a degree in Electrical Engineering and Automation from Northeast Petroleum University in 2019. She was subsequently recommended for a doctoral program in Petroleum and Natural Gas Engineering, during which she also studied at Southeast University, earning her doctorate in 2024.

Professional Experience

Throughout her career, Dr. Na Yi has published over 20 research papers in esteemed journals, with 10 SCI-indexed and 5 EI-indexed papers, including highly cited and hot papers. She holds 6 national patents and has participated in 5 significant scientific research projects. Her achievements have earned her more than 10 national and provincial awards.

Research Interests

Dr. Na Yi’s research interests lie in Petroleum Engineering, with a focus on sustainable energy, power systems, and technological innovation. She is an active reviewer for multiple international and Chinese academic journals and has been invited to present her research at several international and domestic conferences.

 Publications

A multi-stage low-cost false data injection attack method for power CPS

  • Authors: Yi, N., Xu, J., Chen, Y., Pan, F.
  • Journal: Zhejiang Electric Power
  • Year: 2023
A New Distributed Power Supply for Distribution Network Considering SOP Access
  • Authors: Peng, C., Xu, J., Zhao, S., Yi, N.
  • Year: 2023
Multi-stage coordinated cyber-physical topology attack method based on deep reinforcement learning
  • Authors: Yi, N., Xu, J., Chen, Y., Sun, D.
  • Journal: Electric Power Engineering Technology
  • Year: 2023
A multi-stage game model for the false data injection attack from attacker’s perspective
  • Authors: Yi, N., Wang, Q., Yan, L., Tang, Y., Xu, J.
  • Journal: Sustainable Energy, Grids and Networks
  • Year: 2021
Insulator Self-Explosion Defect Detection Based on Hierarchical Multi-Task Deep Learning
  • Authors: Xu, J., Huang, L., Yan, L., Yi, N.
  • Journal: Diangong Jishu Xuebao/Transactions of China Electrotechnical Society
  • Year: 2021

Ms. Mina Gachloo | Machine Learning | Best Researcher Award

Ms. Mina Gachloo | Machine Learning | Best Researcher Award

Mina Gachloo at university of North Carolina Wilmington, United States

Profiles

Scopus

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Google Scholar

Education:

Ms. Mina Gachloo is set to graduate with a Master's degree in Computer Science and Information Systems from the University of North Carolina Wilmington in December 2024, boasting a GPA of 3.8. Her research at UNCW, under the guidance of Dr. Yang Song, focuses on "Temporal Prediction of Coastal Water Quality Based on Environmental Factors with Deep Learning." Mina also holds a Bioinformatics Engineering degree from Huazhong Agricultural University in Wuhan, China, where she researched "Embedding of Cancer-Centric Entities and Knowledge Discovery." Additionally, she earned a B.Sc. in Information Technology from the University of Applied Science and Technology in Tehran, and an Associate’s degree in Information and Communication Technology from the University of Culture and Art in Tehran.

Professional Experience:

Ms. Mina has a diverse range of professional experiences. In 2023, she interned as a Data Analyst and Researcher at the UNCW Institutional Research Office, focusing on predicting the time-to-graduate for undergraduate students. As a Teaching and Research Assistant at UNCW, she conducted data cleaning, feature engineering, and implemented machine learning and deep learning models for predictive analysis. Prior to this, she worked as a Commercial Expert at Bam Khodro Company in Tehran, using SQL, Excel, and Python for data extraction, analysis, and report automation. Mina also served as a Financial Expert at Mellat Leasing Bank, facilitating loans and generating customer reports. Her career began in IT at KICCC in Tehran, specializing in Point of Sale devices and Business Intelligence.

Research Interest:

Ms. Mina's research interests include machine learning, deep learning, structure learning, data analysis, natural language processing, and computer vision. She has actively contributed to several projects, such as the construction of the Active Gene Annotation Corpus (AGAC) and the prediction of dissolved oxygen and salinity levels in the Neuse River Estuary using deep learning techniques.

Honors and Awards:

Ms. Mina's academic excellence has been recognized with multiple awards, including the Summer Research Stipend, Support for Undergraduate Research and Creativity Awards (SURCA), and CMS summer stipend at UNCW. She also received scholarships for her M.Sc. in Computer Science and Bioinformatics at Huazhong Agricultural University.

💡 Skills:

Ms. Mina is proficient in data preprocessing, machine learning, deep learning, natural language processing, and programming in Python and Java. She is skilled in using tools like Jupyter Notebook, Google Colab, Pycharm, IDLE, Microsoft Office, Pegasus, SQL, and Oracle.

 Publications:

Using Machine Learning Models for Short-Term Prediction of Dissolved Oxygen in a Microtidal Estuary
  • Authors: Mina Gachloo, Qianqian Liu, Yang Song, Guozhi Wang, Shuhao Zhang, Nathan Hall
  • Year: 2024
An overview of the active gene annotation corpus and the BioNLP OST 2019 AGAC track tasks
  • Authors: Yuxing Wang, Kaiyin Zhou, Mina Gachloo, Jingbo Xia
  • Year: 2019
A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition
  • Authors: Mina Gachloo, Yuxing Wang, Jingbo Xia
  • Year: 2019
GOF/LOF knowledge inference with tensor decomposition in support of high order link discovery for gene, mutation and disease
  • Authors: Kai Yin Zhou, Yu Xing Wang, Sheng Zhang, Mina Gachloo, Jin Dong Kim, Qi Luo, Kevin Bretonnel Cohen, Jing Bo Xia
  • Year: 2019
An active gene annotation corpus and its application on anti-epilepsy drug discovery
  • Authors: Yuxing Wang, Kaiyin Zhou, Jin-Dong Kim, Kevin B Cohen, Mina Gachloo, Yuxin Ren, Shanghui Nie, Xuan Qin, Panzhong Lu, Jingbo Xia
  • Year: 2019

Dr. Irsa Sajjad | Machine Learning | Best Researcher Award

Dr. Irsa Sajjad, Machine Learning, Best Researcher Award

Doctorate at Central South University, China

Profiles

Scopus

Google Scholar

🌍 Academic Background:

Dr. Irsa Sajjad is a Research Scholar at Central South University, Changsha, China, known for her expertise in hybrid choice modeling and machine learning. Her innovative research integrates deep learning and attention mechanisms, significantly advancing methodologies and applications in the field.

🎓 Education:

Dr. Irsa’s academic background is marked by advanced studies in machine learning and choice modeling, equipping her with a comprehensive understanding of both theoretical concepts and practical applications in her field.

👩‍🏫 Professional Experience:

Dr. Irsa has actively contributed to significant research projects, including developing novel hybrid choice models and Gaussian mixture models. She has collaborated with industry partners on machine learning applications and data visualization techniques and is currently publishing a book on advanced choice modeling.

🔬 Research Interests:

Dr. Irsa’s research interests center on Hybrid Choice Models (HCM), particularly those incorporating attention mechanisms, deep learning, and latent class analysis. Her work aims to enhance the accuracy and effectiveness of choice modeling by addressing complex data structures and improving analytical insights.

📖 Publications:

Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution
  • Authors: Al-Aziz, S.N., Sajjad, I., Dar, J.G., El Bagoury, A.A.-A.H.
  • Journal: International Journal of Neutrosophic Science
  • Year: 2023
Quantile regression-ratio-type estimators for mean estimation under complete and partial auxiliary information
  • Authors: Shahzad, U., Hanif, M., Sajjad, I., Anas, M.M.
  • Journal: Scientia Iranica
  • Year: 2022
Mathematical Simulation and Numerical Computation of the Temperature Profiles in the Peripherals of Human Brain during the Tepid Sponge Treatment to Fever
  • Authors: Aijaz, M., Dar, J.G., Almanjahie, I.M., Sajjad, I.
  • Journal: Computational and Mathematical Methods in Medicine
  • Year: 2022
Imputation based mean estimators in case of missing data utilizing robust regression and variance–covariance matrices
  • Authors: Shahzad, U., Al-Noor, N.H., Hanif, M., Sajjad, I., Muhammad Anas, M.
  • Journal: Communications in Statistics: Simulation and Computation
  • Year: 2022
A new family of robust regression estimators utilizing robust regression tools and supplementary attributes
  • Authors: Sajjad, I., Hanif, M., Koyuncu, N., Shahzad, U., Al-Noor, N.H.
  • Journal: Statistics in Transition New Series
  • Year: 2021

Mr. Nikolaos Argirusis | Machine Learning | Industry Impact Award

Mr. Nikolaos Argirusis, Machine Learning, Industry Impact Award

Nikolaos Argirusis at mat4nrg GmbH, Germany

Profiles

Scopus

Orcid

🎓Education:

Mr. Nikolaos Argirusis pursued his education at Ostfalia University of Applied Sciences, specializing in Energy Systems and Environmental Engineering, achieving a “Very Good” rating in his Master’s degree. Previously, he completed his Bachelor’s in Electrical and Information Technology at Ostfalia University, with a focus on Electromobility and Energy Technology. He also holds a Bachelor’s degree in Electrical Engineering from Technische Universität Braunschweig, specializing in Energy Technology.

💼 Work Experience:

Currently, Nikolaos serves as a Student Assistant at CZM – TU Clausthal, where he contributes to electronics development and plasma technology experiments. He also engages in a research project for mat4nrg GmbH, focusing on prototype development and project organization. As the Co-founder and Managing Director of mat4nrg GmbH, he oversees the management, supervision, and development of research and customer projects. Additionally, Nikolaos supports his family’s business, aeras GmbH, focusing on power electronics assembly.

🌐 Skills and Languages:

He possesses advanced skills in Microsoft Office, PSpice, and LTspice, with foundational knowledge in C++ and Java programming languages. Fluent in German and Greek, Nikolaos also communicates proficiently in English.

🎯 Interests:

Outside of academics and professional endeavors, Nikolaos enjoys swimming, team sports, and engaging in DIY projects, reflecting his diverse interests and active lifestyle.

📖 Publications:

Evaluation of the effectiveness and performance of environmental impact assessment studies in Greece
  • Authors:Papamichael, I., Tsiolaki, F., Stylianou, M., Argirusis, C., Zorpas, A.A.
  • Journal:Comptes Rendus Chimie
  • Year: 2023
End-of-Life Management and Recycling on PV Solar Energy Production
  • Authors:Papamichael, I., Voukkali, I., Jeguirim, M., Argirusis, C., Zorpas, A.A.
  • Journal: Energies
  • Year: 2022
Research Progress in Metal-Organic Framework Based Nanomaterials Applied in Battery Cathodes
  • Authors: Mechili, M., Vaitsis, C., Argirusis, N., Zorpas, A.A., Argirusis, C.
  • Journal: Energies
  • Year: 2022
Research progress in transition metal oxide based bifunctional electrocatalysts for aqueous electrically rechargeable zinc-air batteries
  • Authors: Mechili, M., Vaitsis, C., Argirusis, N., Sourkouni, G., Argirusis, C.
  • Journal: Renewable and Sustainable Energy Reviews
  • Year: 2022
MOF nanomaterials for battery cathodes
  • Authors: Vaitsis, C., Mechili, M., Pandis, P.K., Argirusis, N., Sourkouni, G.
  • Year: 2022